Project Analyst Applications Now Open!
_________________
Developing the trading strategies of tomorrow
We're the idea engine behind CU Quants' trading operations. Our team explores new strategies, analyzes market patterns, and develops the quantitative models that power our live trading systems.
At CUQuants, our research initiatives bridge the gap between academic theory and practical implementation in quantitative finance. We focus on developing innovative methodologies for market microstructure analysis, risk management in illiquid markets, and algorithmic trading strategies that create genuine value in complex financial environments.
Our Approach: We combine rigorous academic research with practical market insights, ensuring our findings contribute meaningfully to both scholarly literature and real-world trading applications.
Head of Research - Magnus Miller and Ryan Watts
Quantitative Researcher - Melanie Fouque
Quantitative Researcher - Samuel Hagen
Quantitative Researcher - JJ Dennis
Quantitative Researcher - Anthony Adams
Quantitative Developer - Jose Camacho
Our interdisciplinary research spans multiple domains within quantitative finance, with particular emphasis on emerging markets and innovative trading strategies.
Investigating price formation mechanisms, liquidity dynamics, and market efficiency in illiquid assets. Our work focuses on understanding how traditional market microstructure theory applies to less liquid markets.
Developing and testing novel algorithmic approaches for market making, statistical arbitrage, and momentum strategies, with particular focus on risk-adjusted performance optimization.
Creating adaptive risk management frameworks that account for the unique characteristics of illiquid markets, including tail risk modeling and stress testing methodologies.
Applying advanced machine learning techniques to financial prediction problems, including deep learning for market prediction and reinforcement learning for trading strategies.
Researching the incorporation of non-traditional data sources into trading and risk models, including social media sentiment, satellite data, and economic indicators.
Analyzing the unique properties of digital asset markets, including volatility patterns, market structure differences, and regulatory impacts on price formation.
You can explore more details about our methodologies and findings on our Research and Publications Page.